EAA Web Session: A Machine Learning Approach to Best Estimate Assumption Setting - Life Insurance Case Study
Announcement from the EAA organiser:
This web session will explore how Python's Machine Learning libraries and Explainable AI (XAI) techniques can be used to enhance best estimate assumption setting in life insurance. Attendees will gain an understanding of the intersection between Machine Learning, XAI, and actuarial science, with a focus on practical applications and real-world case studies.
Topics Covered:
- An introduction to Machine Learning concepts relevant to life insurance assumption setting.
- Demonstration of Python libraries for exploratory data analysis and model building.
- Step-by-step guidance on building, training, and validating predictive models for assumption setting.
- Techniques to mitigate against overfitting
- Evaluation metrics to assess model performance
- Explainable AI techniques to ensure transparency and interpretability of Machine Learning models.
- Examples of successful implementations in assumption setting.
- Best practices and common pitfalls in integrating Machine Learning and XAI into actuarial processes.
Click here to register. Your early-bird registration fee is € 150.00 (net) / € 178.50 (incl. VAT, if applicable) until 17 December 2024. After this date, the fee will be € 195.00 (net) / € 232.05 (incl. VAT, if applicable).
Click here. (Note: timing via that link is in CEST [Central European Summer Time].)
Jennifer is an actuary and accountant with over 20 years’ experience in the insurance industry. She currently serves as Executive Director, Group CFO, Chief Risk Officer and Head of Actuarial Function with Acorn Life in Ireland. She is also an Independent Non Executive Director of Vhi, the Irish state-owned health insurer. Jennifer is a Fellow of the Institute and Faculty of Actuaries (UK), the Society of Actuaries in Ireland and the Association of Chartered Certified Accountants. She is a member of the IFoA Actuarial Data Science Working Group and is an active member of the Society of Actuaries in Ireland through the Data Science Committee and the Diversity, Equity, Accessibility and Inclusion Committee. Jennifer holds an MSc in Data Analytics and is an Ambassador for Women in Data Science.